Analysis of Different Multiobjective Optimization Scenarios in Estimating the Adjustable Parameters of a Generalized Cubic Equation of State

Since the emergence of the van der Waals model, a lot of equations of state have been proposed to represent the pressure-volume-temperature (PVT) behavior of pure compounds, as is the case with GEOS3C, which is a form of generalized cubic equation of state that uses a temperature function dependent on three adjustable parameters. As the predictive capacity of an equation of state is directly related to the use of adequate and efficient methods for estimating the model's parameters, it is advised to use the multiobjective optimization in this class of problems, due to the conflicting nature of the objective functions. In this context, a MOPSO algorithm, based on the Pareto dominance principle, is used to estimate the parameters of the GEOS3C, through the minimization of the deviations in the prediction of different thermodynamic properties: saturation pressure, saturated liquid volume, enthalpy of vaporization and isobaric heat capacity, in order to assess whether it is possible to obtain a model parameterization that is adequate to represent the different properties simultaneously. Comparisons with experimental data available in the literature are performed showing that multiobjective optimization offers new perspectives for improvements in the parameters estimation of equations of state compared to traditional methods.